Model-Based Conditional Weighted Residuals Analysis for Structural Model Assessment.

ABSTRACT: Nonlinear mixed effects models are widely used to describe longitudinal data to improve the efficiency of drug development process or increase the understanding of the studied disease. In such settings, the appropriateness of the modeling assumptions is critical in order to draw correct conclusions and must be carefully assessed for any substantial violations. Here, we propose a new method for structure model assessment, based on assessment of bias in conditional weighted residuals (CWRES). We illustrate this method by assessing prediction bias in two integrated models for glucose homeostasis, the integrated glucose-insulin (IGI) model, and the integrated minimal model (IMM). One dataset was simulated from each model then analyzed with the two models. CWRES outputted from each model fittin

SUBMITTER: Ibrahim MMA 

PROVIDER: S-EPMC6394649 | biostudies-literature | 2019 Feb

REPOSITORIES: biostudies-literature